Triple

T60150
Position Surface form Disambiguated ID Type / Status
Subject Kathy Hochul E1192 entity
Predicate givenName P17 FINISHED
Object Kathy
Kathy is the given name of Kathy Hochul, the 57th governor of New York and the first woman to hold that office.
 E23141 NE FINISHED

How this triple was built (4 steps)

Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.

NER Named-entity recognition gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: Kathy | Statement: [Kathy Hochul, givenName, Kathy]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Kathy
Context triple: [Kathy Hochul, givenName, Kathy]
  • A. Katherine Rogers
    Katherine Rogers was the mother of John Harvard, the English clergyman whose bequest helped found Harvard College in colonial Massachusetts.
  • B. Barbara
    Barbara is a feminine given name of Greek origin that has been widely used in many cultures and languages.
  • C. Mary Easty
    Mary Easty was a respected Salem, Massachusetts woman who was falsely accused of witchcraft and executed during the 1692 Salem witch trials, later remembered for her dignified plea for justice.
  • D. Angela
    Angela is the given name of Angela Merkel, the long-serving former Chancellor of Germany and a prominent European political leader.
  • E. Nance
    Nance is the middle name of John Nance Garner, the 32nd vice president of the United States under Franklin D. Roosevelt.
  • F. None of above. chosen
  • G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg Description generation gpt-5.1
Instruction
Generate a one-sentence description of the target entity. 
You are given a context triple in the form (subject, predicate, object), where the object is the target entity. 
# Instructions
Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. 
Avoid repeating the information from the triple, unless really essential.
# Response Format
Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Kathy
Triple: [Kathy Hochul, givenName, Kathy]
Generated description
Kathy is the given name of Kathy Hochul, the 57th governor of New York and the first woman to hold that office.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Kathy
Target entity description: Kathy is the given name of Kathy Hochul, the 57th governor of New York and the first woman to hold that office.
  • A. Katherine Rogers
    Katherine Rogers was the mother of John Harvard, the English clergyman whose bequest helped found Harvard College in colonial Massachusetts.
  • B. Barbara
    Barbara is a feminine given name of Greek origin that has been widely used in many cultures and languages.
  • C. Mary Easty
    Mary Easty was a respected Salem, Massachusetts woman who was falsely accused of witchcraft and executed during the 1692 Salem witch trials, later remembered for her dignified plea for justice.
  • D. Angela
    Angela is the given name of Angela Merkel, the long-serving former Chancellor of Germany and a prominent European political leader.
  • E. Nance
    Nance is the middle name of John Nance Garner, the 32nd vice president of the United States under Franklin D. Roosevelt.
  • F. None of above. chosen

Provenance (5 batches)

The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.

Step Stage Batch ID Status When
creating Elicitation batch_69a24a552ef88190a0df287d68c65cba completed Feb. 28, 2026, 1:52 a.m.
NER Named-entity recognition batch_69a24ec5f46081909f3ba0b25190282b completed Feb. 28, 2026, 2:11 a.m.
NED1 Entity disambiguation (via context triple) batch_69a2fa77f01081908738405e28c789d8 completed Feb. 28, 2026, 2:23 p.m.
NEDg Description generation batch_69a2fbd4e3388190925a18311006d485 completed Feb. 28, 2026, 2:29 p.m.
NED2 Entity disambiguation (via description) batch_69a2fc273f4081909420d40b9e8b7c5a completed Feb. 28, 2026, 2:31 p.m.
Created at: Feb. 28, 2026, 1:55 a.m.